Background
The aim of this study was to test the effectiveness, safety and stability of the 5G communication technology in clinical laparoscopic telesurgery.
Methods
An ultra‐remote radical cystectomy (network communication distance of nearly 3000 km) was performed on patient diagnosed with T2N0M0 stage bladder cancer using a domestically produced “MicroHand” surgical robot.
Results
The network delay, operative time, blood loss, intraoperative complications, postoperative recovery, and hospitalisation time were recorded. The 5G network was used throughout the operation, with an average total delay of 254 ms. The operation went well and the patient recovered smoothly.
Conclusions
Ultra‐remote clinical laparoscopic surgery can be performed safely and smoothly. More importantly, our model can provide insights for promoting the future development of telesurgery in China.
Background: Deterministic Networking (DetNet) is a new technology that can effectively control network delay and may promote the revolution of telemedicine.This study verified the feasibility and advantage of deterministic networking in telesurgery.Methods: All telesurgeries employed the 'MicroHand S' surgical robot system. The network mode adopted fixed-line and 5G wireless networks, while the network configuration scheme adopted DetNet and general networking. The telesurgery data of three patients using DetNet and four patients using a general network were collected, and the time-delay, packet loss rate and delay jitter were compared during the operations.Results: Compared with a general network, DetNet can effectively control data transmission during the telesurgery process for both fixed-line and 5G wireless networks, further reducing network latency, minimising data fluctuations, and improving surgery security.
Conclusion:The DetNet meets the requirements of deterministic delay, low jitter and high bandwidth for telesurgery, which may provide effective network guarantee for developing the telemedicine system.
Background
Inflammatory response biomarkers have been studied as promising prognostic factors in renal cell carcinoma, but few studies have focused on papillary renal cell carcinoma (PRCC). This study was performed to evaluate the prognostic value of the preoperative neutrophil-to-lymphocyte ratio (NLR) in PRCC patients.
Methods
In total, 122 postoperative PRCC patients selected from 366 non-clear cell renal cell carcinoma patients were enrolled from our institution between 2012 and 2020. The optimal cutoff value of the NLR was assessed by receiver operating characteristic (ROC) curve analysis, and the Kaplan–Meier method and Cox's proportional hazards regression models were performed to analyze the association of the NLR with overall survival (OS). In addition, the potential of tumor-node-metastasis (TNM) stage, the NLR and an NLR-TNM system to predict survival were compared with ROC curves, and clinical usefulness of the predicting models were assessed by decision curve analysis.
Results
A threshold value of 2.39 for the NLR for OS analysis was determined by ROC curve analysis. An NLR ≥ 2.39 was associated with a more advanced TNM stage (P < 0.01) and larger tumors (P < 0.05) than a low NLR, as well as pathological subtype II (P < 0.05), and the patients with a high NLR also exhibited significantly worse overall survival outcomes (P < 0.05). The NLR was determined to be a significant independent prognostic indicator by univariable and multivariable analyses (HR = 5.56, P < 0.05). Furthermore, TNM stage and the NLR were integrated, and the area under the curve (AUC) of for the NLR-TNM system was larger than that of for the TNM system when predicting overall survival (0.84 vs 0.73, P = 0.04). Decision curve analysis also demonstrated a better clinical value for the NLR-TNM model to predict the prognosis.
Conclusion
A high preoperative NLR was associated with poor clinical and pathologic parameters in patients with PRCC; moreover, the NLR was also an independent prognostic factor for the OS of patients with PRCC. The NLR-TNM system, which was a model that integrated the NLR with TNM staging, could improve the ability to predict overall survival.
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